In the highly congested crowd scene, the regression-based methods are usually chosen. They have two important stages. The low-level features are first extracted from the input image, then the crowd count is regressed according to the low-level features. To record the space information of the crowd, Lempitsky et al. [1]} proposed a good method that could learn a linear mapping between local area features and corresponding density maps. Based on Lempitsky's work, Pham et al. [2]} proposed a more applicable method. The linear mapping was replaced with a non-linear mapping based on random forest regression. In [3]}, SVM is proposed to map the features extracted by AdaBoost [4]} to the crowd counting result.
